SPLC 2018 Challenge

Localizing Configurations in Highly-Configurable Systems

Paul Gazzillo, University of Central Florida, USA
Ugur Koc, University of Maryland, USA
ThanhVu Nguyen, University of Nebraska-Lincoln, USA
Shiyi Wei, University of Texas at Dallas, USA
The complexity of configurable systems has grown immensely, and it is only getting more complex. Such systems are a challenge for software testing and maintenance, because bugs and other defects can and do appear in any configuration. One common requirement for many development tasks is to identify the configurations that lead to a given defect or some other program behavior. We distill this requirement down to a challenge question: given a program location in a source file, what are valid configurations that include the location? The key obstacle is scalability. When there are thousands of configuration options, enumerating all combinations is exponential and infeasible. We provide a set of target programs of increasing difficulty and variations on the challenge question so that submitters of all experience levels can try out solutions. Our hope is to engage the community and stimulate new and interesting approaches to the problem of analyzing configurations.


PCLocator: A Tool Suite to Automatically Identify Configurations for Code Locations

Elias Kuiter, Sebastian Krieter, Jacob Kr├╝ger, Kai Ludwig, Thomas Leich, and Gunter Saake
SPLC 2018 Solution
The source code of highly-configurable software is challenging to comprehend, analyze, and test. In particular, it is hard to identify all configurations that comprise a certain code location. We contribute PCLocator, a tool suite that solves this problem by utilizing static analysis tools for compile-time variability. Using BusyBox and the Variability Bugs Database (VBDb), we evaluate the correctness and performance of PCLocator. The results show that we are able to analyze files in a matter of seconds and derive correct configurations in 95% of all cases.
Solution paper


No discussion section for the moment.